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On estimation of the PDF and the CDF of the one-parameter polynomial exponential family of distributions
被引:5
|作者:
Mukherjee, Indrani
[1
]
Maiti, Sudhansu S.
[1
]
Singh, Vijay Vir
[2
]
机构:
[1] Visva Bharati Univ, Dept Stat, Santini Ketan 731235, W Bengal, India
[2] Yusuf Maitama Sule Univ, Fac Sci, Dept Math, Kano, Nigeria
关键词:
Lindley distribution;
maximum likelihood estimator;
uniformly minimum variance unbiased estimator;
D O I:
10.1080/03610926.2021.1910302
中图分类号:
O21 [概率论与数理统计];
C8 [统计学];
学科分类号:
020208 ;
070103 ;
0714 ;
摘要:
In this article, we have considered the estimation of the probability density function and cumulative distribution function of the one-parameter polynomial exponential family of distributions. A number of probability distributions like the exponential, Lindley, length-biased Lindley and Sujatha are particular cases. Two estimators-maximum likelihood and uniformly minimum variance unbiased estimators of the probability density function and cumulative distribution function of the family have been discussed. The estimation issues of the length-biased Lindley and Sujatha distribution have been considered in detail. The estimators have been compared in mean squared error sense. Monte Carlo simulations and real data analysis are performed to compare the performances of the proposed estimators.
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页码:104 / 120
页数:17
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